The National Institute
for Complex Data Structures

 

News about the NICDS Re-Application

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The NICDS is a national institute whose mandate is to enrich and enlarge the national research enterprise through a powerful new model for the statistical sciences. The NICDS fosters nationally coordinated projects with statistical leadership and a substantial interaction with researchers in science and health. Projects advance research frontiers in other disciplines through the development of novel methods for large-scale problems involving complex data sets.

The NICDS receives its primary support form the Natural Sciences and Engineering Research Council of Canada.

THE NATIONAL INSTITUTE FOR COMPLEX DATA STRUCTURES (NICDS) SOLICITS PROPOSALS FOR INAUGURAL WORKSHOPS.

The NICDS is soliciting proposals for inaugural workshops to take place in 2009. Proposals should emphasize the development and application of statistical methods for the analysis of data with complex structures. Such data arise in a wide variety of settings including, but not limited to, surveys with complex designs, biological, environmental, medical or industrial studies with longitudinal or hierarchical structures, and many areas of the physical sciences. An important goal for successful workshops is the development of a scientific collaboration and proposal for funding to NICDS and related organizations. Please consult the NICDS scientific activities webpage for detailed instructions, guidelines, an application template and evaluation criteria.

The deadline for applications is November 30, 2008 and any questions may be directed to Jamie Stafford, the NICDS director (email link) . Applicants are advised to seek assistance in the preparation of their proposal.

The National Institute for Complex Data Structures is a development of the National Program on Complex Data Structures (NPCDS), and receives funding from NSERC and from the Universities of British Columbia, Manitoba, Simon Fraser, Toronto, Western Ontario, and Waterloo. We have funded eight national projects, on topics ranging from survey sampling, to spatial data in forestry, to longitudinal data for public health, to climate statistics for agriculture.

 

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